The Aging Athlete (2) – 100m

How do Sprinters age? When does the aging effect on our speed really begin to increase its decline? Is the timing different women vs men? It’s probably neither consistent nor smooth. I’ve often heard it said that we, on average, lose 1% a year. Is this speed? Or endurance? Or both? I don’t know, but let’s see what the data appears to say.

I’m going to start with the 100m, which should be a good reflection of how “speed” declines with age.  I am using the duncanSCORE data base which contains 8,626 Women’s 100m entries up to and including W75 and 21,540 Men’s 100m performances (from mastersrankings.com for the years 2013-2016) used to calculate our scores and percentiles (if you are interested, you can get the details of the data processing here). Beyond W75  and M85 the numbers of performances are too sparse to use in our analysis.

The above graph may be a bit small to view properly. Here it is in full size Average    

What we see are some differences Women (in green) vs Men (in blue). Both genders decline in performance (vs the previous age group) generally about the same rate until “55”. This is shown in the tabular section under the graph lines and is labeled “% to Prev” (the percentage decline vs the previous age-group).   At that stage Women slow down 6.6% vs W50s, while M55s are averagely 3.99% slower than M50s.

The Men’s slowdown continues to accelerate (reaching 6.74% slower than the previous age group at M65), but then a sort of miracle happens! See where the blue line flattens a bit? The Men’s rate of decline (3.07%) is less then half the previous, but then accelerates much faster at M75 onward.

Women get their “mini miracle” to happen at W65. There the speed decline does indeed decline (to 4.74% from 6.29%), From there as you can see in the graph, the line begins its 45 degree upward slope. The Men’s roughly 45 degree slope commences at M75.

That’s it in a nutshell. I hope I haven’t bored you to tears, because the next posting will look at the Women’s 100m in more detail.

And don’t forget, to see how you compare against other runners in your age-group, enter your time for your event and see how your performance rates

http://duncanscore.com/track-de/

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If you are new here and this is all a little confusing and really don’t get what I’m talking about, please have a quick read that will explain the concepts behind the duncanSCORE

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Delving Into The Aging Athlete (1)

We all age. That is if we are lucky enough to live so long. And supposedly, we all age at different rates. Probably that is true, but the data showing that is surprisingly light. Tracking aging is particularly important (and interesting!) for Masters athletes.

I am hoping to be able to provide some basic information on how we age as track and field athletes. Unfortunately, what we won’t be able to quantify is the slowdown by individual year ie how much is a 49 year old slower (on average) than a 48 year old. One day I hope enough data will be available for that.

And how does it differ Men versus Women? Or maybe it doesn’t? We will definitely look into that.

And perhaps in the not too distant future, we can look at how top performers tend to do over advancing years versus the average Master. I’m very interested in that.

We will start with the 100m, men and women, using 4 years of mastersrankings.com data (2013-2016). Then we will move on to some other events.

But first 100m. Stay tuned.

To see how your 100m time compares with your age cohort peers click here

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So … How This All Started

above photo courtesy of Dan Slovitt

Header photo courtesy of John MacMillan

The “beginning” for the duncanSCORE was the very late autumn of 2015.  Without going into details, I was on committees that were selecting “Athlete of the Year” in a couple of jurisdictions. My input involved athletes’ successes in terms of medals won at various championships, and records set.

Needless to say athletes in different age groups and across the track and field event spectrum were involved. Picking winner(s) was difficult. Often the discussion came back to “well Abc had an Age Grading of xx.xx% while Xyz‘s Age Grade was only xx.xx-1%”.

After much back and forth, I gave up, infuriated. Comparisons were being made across age groups and events and disciplines, and the Age Grade differences in my mind were insignificant. Knowing that the sample “sizes” for each age year and event were only ONE, and the model created included some manual “tweaking”, I knew this was a very inappropriate use of Age Grading. Believing that an Age Grade to the 1/100 was significant over a similar result from a different age group and event was ludicrous.

There had to be (and needed to be) a better way!

A few days later it started dawning on me. For the last year or so, since he had taken over the masters world rankings from Martin Gasselsberger, John Seto was beginning to amass a treasure trove of Masters’ performances. (For some history on rankings for masters, read this on Ken Stone’s masterstrack blog https://masterstrack.blog/rankings/).

Could these not be used? Perhaps they could be!

I started pulling the data for a few track events and a couple of field events from a single year for a collection of age groups. I wanted to see if it was possible, and moreover, if the results made any sense. They seemed to. I consulted with my coaches Paul Osland and Mike Sherar, and they too thought there was something there.

I pressed on. Adding more age groups and looking at 3 years of data for M50 800m. I added a few more events.

All this took me into the late spring of 2016.

I played around with different scoring systems and ideas. At the same time I started gathering more data. As many years as possible. To this point I have organized 4 years of best performance (2013, 2014, 2015, and 2016). See here the mechanics how it works

I won’t further bore you with all the problems and blind alleys I pursued. Just know I explored a lot of them before deciding on the concept you see today.  I’m a slow learner and worker, but here at last, is a “beta” look at the concept.

For a more in-depth understanding see An Introduction

 

 

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Beginning to Mine the Motherlode

Well, let’s get this going. “This” being the blog part of the duncanSCORE site.

My hope is to post here weekly, with news, updates, and information on duncanSCORE, and associated material. The duncanSCORE is a new wrinkle for Masters Athletics … something different. And I suspect what I write here may be a little different, too.

There is a wealth of information accumulating about Masters track and field performances, and my goal is to be able to mine it a little, and shed more light on our unique attack on aging than has been been historically shone. I would like a few facts to get in the way of some of the “truths” that are out there.

Though likely sometimes data “heavy”, I will try and cut to the chase as quickly as possible to point out the relevant points for us. I’m very excited to be able to begin analyzing all of this incredible data being accumulated. Thanks to John Seto at mastersrankings.com, it’s a motherlode of data on our sport.

Not only do we enjoy the hard training and competing, but we all love and  appreciate the camaraderie that comes along with Masters Athletics. There’s nothing like it! But I also think that by studying the data, there is an opportunity to learn … to help us compete better, and be healthier.

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